One of the difficult aspects of any engineering/design analysis during various design and validation phases in a product cycle is extracting needed data for better understanding the behavior of a device and/or a system. This is especially true with computational data, such as computational fluid dynamics (CFD) data and finite element analysis (FEA) data and so on, that are based on discretization of overall geometry/domain into large number of smaller volumes (called as cells/elements). Such computational data can amount to few millions to hundreds of millions of physical quantities/data (for example, pressure, velocity and temperature data) associated with each smaller volume of the larger volume or an enclosure and it can be seen that this can amount to significantly large amount of computational data. Extracting most relevant data and needed information from such large amount of computational data can be expensive and time consuming.
Generally, only such extracted data is relevant for carrying out the experiments and analysis. Typically, such relevant data is obtained based on heuristic approach, such as historical information or prior experimental information and such data may not be accurate. For example, the relevant data can be used to determine the locations, where the measurements have to be made in an avionics air conditioning system's bay to obtain more meaningful results and gain a better understanding, for carrying out future experimental thermal validations and for analyzing the computational data.